CHAPTER IV: SUBSCRIPTION RENEWAL OF CLOUD ENTERPRISE SYSTEMS
5. RESULTS
5.2. S TRUCTURAL M ODEL
To test the significance of the paths between the latent constructs and therefore to calculate t-values, the bootstrap algorithm was applied with 98 cases and 5000 subsamples (Hair et al.
2011). The results indicate that the constructs accounted for 50.4% of the variance in subscription renewal intention. All paths except for H7 showed significant relationships above the p<.05 level with medium to large effect sizes (Cohen 1988). H6 showed a negative relationship in opposition to the predicted positive correlation. The lack of support for H7 shows that information quality does not contribute to the formation of subscription renewal intention. Total effects of confirmation on subscription renewal intention of .2911 showed a moderate indirect effect. In addition to R² values, predictive relevance was assessed using the
ID Item
Reflective Measures Outer
Loadings t-value
Composite Reliability AVE
Net Benefits (Adapted from Wixom and Todd 2001) 0.91 .77
NB1 Our CES has changed my company significantly. 0.82 11.73
NB2 Our CES has brought significant benefits to the company. 0.92 45.91
NB3* Overall, my CES is beneficial for the company. 0.88 25.07
Confirmation (Adapted from Bhattacharjee 2001) 0.89 .73
CO1 My experience with using our cloud enterprise system was better than what I expected. 0.90 32.02 CO2 The quality of the cloud service provided by our CES was better than what I expected. 0.88 24.71 CO3 Overall, most of my expectations from introducing our CES were confirmed. 0.78 11.41
Subscription Renewal Intention** (Adapted from Bhattacharjee 2001) 0.83 .71
SRI1 We intend to continue the subscription of our CES rather than discontinue ist subscription 0.86 9.33 SRI2 We intend to continue the subscription of our CES than to subscribe to any alternative means. 0.82 9.22
Technical Integration (Adapted from Furneaux and Wade 2011) 0.96 .89
TI1 The technical characteristics of the system make it complex. 0.93 8.62
TI2 The system depends on a sophisticated intergation of technology components. 0.96 9.29 TI3 There is considerable technical complexity underlying this system. 0.94 8.39
System Investment (Adapted from Furneaux and Wade 2011) 0.94 .85
SI1 Significant organizational resources have been invested in this system. 0.84 3.42
SI2 We have commited considerable time and money to the implementation and operation
of the system. 0.96 3.48
SI3 The financial investments that have been made in this system are substantial. 0.96 3.22
Attitude (Adapted from Wixom and Todd 2005) 0.92 .80
AT1 Using our CES is enjoyable. 0.92 51.29
AT2 My attitude toward using our CES is favourable. 0.91 22.41
AT3 Overall, using our CES is pleasent. 0.87 23.63
Information Quality (Adapted from Wixom and Todd 2005) 0.96 .92
IQ1 Overall, I would give the inforamtion from our CES high marks. 0.96 30.97
IQ2 In general, our CES provides me with high-quality information. 0.95 33.69
System Quality (Adapted from Wixom and Todd 2005) 0.97 .94
SQ1 In terms of system quality, I would rate our CES highly. 0.97 138.21
SQ2 Overall, our CES is of high quality. 0.97 93.72
* Newly created
** One item was dropped due to poor psychometric properties.
Items with Loadings and Weights
Quality Criteria
blindfolding procedures to obtain cross-validity redundancy (Chin 1998). Results showed good predictive relevance, with all Q²>0 (Geisser 1975).
Figure 2. Path Model Results sConfirmation
Subscription Renewal Intention
R²=.504 Net Benefits
R²=.291 System
Investment
Technical Integration
System Quality Information
Quality
.540***
(5.740)
.253**
(2.310) -.438***
(2.892) .284**
(1.988) .0032
(0.204)
.278**
(2.410) Attidue
R²=.391 .625***
(9.078)
.247**
(2.540)
* p < .1
** p < .05
*** p < .01
6.
FINDINGS, LIMITATIONS, AND FUTURE RESEARCHWe believe that our model yielded interesting results by being able to explain 50.4% of the variance in subscription renewal intention. Net benefits and system quality showed to have significant impact on the subscription renewal intention of CES. This is not surprising, as the role of IS within companies has often been described as context activity supporting and enabling the company to manage their business processes or to save costs. Surprisingly, however, information quality does not contribute the prediction of subscription renewal intention, even though support of decision making can be seen as one of the major tasks of ES. Given the limited time IT decision makers usually have to spare, the results suggest that CES providers’ sales team should emphasize on the high system quality of the CES, as well as its net benefits for the company. The insignificance of information quality allows synthesizing our findings with the results of Furneaux and Wade (2011), which do not include information quality but system reliability and system performance shortcomings (both dimensions can be seen as sub-dimensions of system quality) as change forces. A possible reason for the insignificance of information quality might lie in the fact that IT decision makers evaluate and therefore judge on “hard system” facts like system uptime, but do not include the quality of information (such as formatting) into their considerations, especially if they are not system users by themselves. From a theoretical viewpoint, the significant path between the IS success dimensions and renewal intention shows a clear linkage between the success of an IS and its organizational continuance. Affective and cognitive responses had a strong influence on the subscription renewal intention, either directly and indirectly. While studies on organizational system continuance have usually cancelled out behavioral factors, our results show that these models can lack validity at least in our context of application – CES - and can significantly contribute to predict subscription renewal intention. As previously outlined, we see the main reasons for the impact of individual behavioral factors on group properties in the fact that decision in the cloud context are usually made by individual decision makers. The results also propose that it is possible to structure the constructs according to TRB as individual behavioral mechanism, where net benefits and confirmation can be seen as behavioral beliefs, the system and information quality as external variables, attitude as affect and continuation inertia as influencing perceived behavioral control. As result, TPB would provide a single theoretical lens structuring the findings.
Practical implications for the influence of affective and cognitive responses can be found in marketing literature, where attitudes can be manipulated separately from service itself, e.g. by
creating brand awareness or a well-managed customer relationship management.
Additionally, the strong impact of confirmation shows that expectations might not be set too high, as they might then be disconfirmed. From a theoretical viewpoint, our study suggests that attitude is a significant predictor of subscription renewal intention making it necessary to re-think organizational system continuance in the context of CES (or generally). Continuation inertia showed to significantly influence subscription renewal intention. This is especially interesting in the context of cloud computing, as cloud computing has seen a strong labeling towards low up-front investments, system flexibility, low entrance barrier, etc. Our study opposes the generalizability of this view in the context of CES. Especially implementation and personnel training costs of CES are still substantial investments, posing severe barriers on changing or discontinuing a cloud service. Contrary to Furneaux and Wade (2011) we find a significant relationship of system investment, which might be due to the fact that we are looking at an earlier stage of the lifecycle. Cloud service providers should clarify the amount of implementation costs which are to be expected within the implementation phase to reduce frustration. Technical integration showed to have a negative impact on subscription renewal intention, contrary to our prediction. The reason for this can be that technical integration is no direct predictor of behavioral intention, but influences system satisfaction negatively as conceptualized by Wixom and Todd (2005). As we used PLS, another reason could be that other influences are relatively stronger. This work has several limitations which need to be discussed. First, it is important to highlight that our measurement was based on the view of individuals reporting about organizational properties and their affective and cognitive responses. It may thus be argued that the dependent variable in our model might be biased given that it reflects an individual perspective rather than a shared opinion within the organization. This problem has been highlighted by several prior studies (e.g. Benlian et al.
2011; Furneaux and Wade 2011) studying organizational system continuance. However, we believe that this problem is less severe in our study, as it is likely that in the context of CES, organizational system continuance is typically decided by an individual or a small number of individuals. Second, even though we were able to explain a decent portion of variance in the target construct, there might be factors which we did not include but are relevant (e.g. internal pressures). Even though risks have been often studied in the adoption phase, the novelty of cloud computing might also raise awareness after the system has been adopted (Benlian and Hess 2011). Therefore future research might draw on these variables. Third, as we conducted a cross-sectional study, we are not able to see how good our model tests actual behavior.
Additionally, we draw the directions of our causalities from theoretical assumptions, which cannot be empirically validated. Therefore future research should include “hard data” to limit biases which are connected to survey methods. Finally, our sub-samples should consider different ES, firm sizes, implementation times and industries. Clustering these sub-samples might lead to more specific insights about specific industries or ES, i.e., the role of system investment for less complex ES.
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